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Durex latex condom used for contraception and for prophylactic purposes (to help prevent pregnancy and the transmission of sexually transmitted disease).

The condom is made of a natural rubber latex sheath, which completely covers the penis with a closely fitted membrane. The device is a shaped, teat ended, lubricated condom which is lubricated with a water based warming lubricant.

This document is a 510(k) premarket notification for a Durex Male Latex Condom with Warming Lubricant. It does not describe a study that proves the device meets acceptance criteria in the way a medical device AI/algorithm submission would. Instead, it demonstrates substantial equivalence to predicate devices based on conformity to existing standards and physical testing.

Here's an analysis of the provided text in the context of your request, highlighting what is and isn't present:

This submission is for a physical medical device (condom with lubricant), not an AI/algorithm. Therefore, many of the requested criteria regarding AI performance studies (e.g., sample size for test set, number of experts, adjudication method, MRMC studies, standalone performance) are not applicable or described in the provided text.

However, I can extract the relevant information regarding the device's conformance to standards and the basis for its safety and effectiveness.

Acceptance Criteria and Reported Device Performance (as much as can be inferred):

Explanation of the Study and Device Conformance (where applicable):

1. A table of acceptance criteria and the reported device performance
   See table above. The document states, "The device is designed to conform to national and international voluntary standards, including ISO 4074 and ASTM D3492, except where noted." And for the finished product, "Physical testing and release testing of the finished product revealed results in conformance with required specifications."

2. Sample size used for the test set and the data provenance
   Not explicitly stated in the provided text. For a physical device, testing involves material properties and functional tests, often using batches or statistical samples, which are not detailed here.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
   Not applicable as this is not an AI/algorithm submission requiring expert-established ground truth. Conformance to standards is the primary "ground truth" for this type of device.

4. Adjudication method for the test set
   Not applicable as this is not an AI/algorithm submission.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
   Not applicable. This is a physical device, not an AI/algorithm.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
   Not applicable. This is a physical device, not an AI/algorithm.

7. The type of ground truth used
   The "ground truth" for this device's acceptance is its conformance to established national and international voluntary standards (ISO 4074 and ASTM D3942) and its physical/release testing specifications.

8. The sample size for the training set
   Not applicable. There is no AI/algorithm training set for this physical device.

9. How the ground truth for the training set was established
   Not applicable. There is no AI/algorithm training set. The "ground truth" for the device's safety and effectiveness is established through its design, materials, manufacturing processes, and testing that demonstrate conformance to recognized engineering and product standards for condoms and lubricants. The substantial equivalence argument relies on comparing these characteristics to legally marketed predicate devices.

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